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Tipping points: From patterns to predictions

There has been much talk about tipping points over the past few years, and about the warning signals that may precede them. You could be forgiven for thinking that the forecasting of epidemics and stock-market crashes is just around the corner. But no one has yet managed to use the theory on early warning signals to predict a natural catastrophe.

The rewards of bridging the gap between the real world and mathematical conceptualizations of catastrophic shifts would be vast. Climate scientists might be able to foresee major shifts in the ocean currents with a rise in global temperatures; ecologists could potentially stave off pest outbreaks; and policies might be implemented to avert the collapse of fisheries1. (A report out this week from the World Economic Forum outlines other risks facing the world2). But for such applications to emerge, researchers should resist the lure of general rules. We must instead use all the available data to develop tools to study the specific properties of real systems.

 

Tipping points: From patterns to predictions

Carl Boettiger & Alan Hastings

Nature 493, 157–158 (10 January 2013) http://dx.doi.org/10.1038/493157a

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When Networks Network

When Networks Network | Papers | Scoop.it

When networks depend on other networks, such as a communications network that relies on a power grid, failure can cascade back and forth between the two. This behavior may explain sudden breakdowns in interacting systems. Thus, the effects of an attack on a single node can reduce an übernetwork  that starts with 12 operating nodes to just four.

Once studied solo, systems display surprising behavior when they interact.

 


Via FuturICT
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